EIT-guided chest physiotherapy for airway clearance during awake prone ventilation in ARDS: a randomized controlled trial

Introduction

Since its introduction in the 1970s, prone position ventilation has been proven effective in the management of acute respiratory distress syndrome (ARDS) (1). By promoting dorsal lung recruitment, this technique improves ventilation-perfusion matching, reduces mechanical stress on the lungs, and enhances oxygenation (2,3). Its clinical value was further underscored during the coronavirus disease 2019 (COVID 19) pandemic, which prompted widespread adoption of prone positioning in critical care settings (4).

In recent years, awake prone positioning (APP) has emerged as a frontline intervention for non-intubated patients receiving high-flow nasal oxygen therapy or noninvasive ventilation. The approach aims to improve oxygenation and delay progression to invasive mechanical ventilation. However, failure rates remain substantial, ranging from 22% to 31% (5,6), highlighting the need for more effective supportive strategies.

Airway clearance is a critical yet often under-optimized component of intensive care unit (ICU) respiratory management. Conventional methods—such as auscultation, chest radiography, and computed tomography—are widely used but limited by issues of sensitivity, specificity, and feasibility in critically ill patients (7). These limitations underscore the need for more dynamic and individualized monitoring tools.

Electrical impedance tomography (EIT) offers a promising alternative. As a noninvasive, bedside-compatible imaging modality, EIT enables continuous, real-time assessment of lung ventilation and perfusion (8). When integrated into airway clearance protocols, EIT may facilitate more targeted and responsive respiratory care, particularly in patients undergoing awake prone ventilation.

This study investigates whether an EIT-guided airway clearance protocol can enhance oxygenation, improve patient comfort, and optimize clinical outcomes in ICU patients receiving awake prone ventilation. Specifically, we examine whether real-time lung monitoring via EIT can reduce failure rates and improve respiratory performance compared to standard clearance practices.

We hypothesize that incorporating EIT into the airway clearance workflow will yield measurable improvements in short-term oxygenation and overall patient outcomes. We present this article in accordance with the CONSORT reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1473/rc).

Methods

Ethical considerations

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Tianjin Third Central Hospital (No. IRB2024-038-02) and informed consent was obtained from all participants or their legally authorized representatives. Privacy and data confidentiality were strictly maintained throughout the study. All participants retained the right to withdraw at any time without any impact on their medical care.

Study design

A prospective, parallel-group, randomized controlled trial was conducted in the ICU of a tertiary hospital in Tianjin. Participants were randomly assigned in a 1:1 ratio to either the experimental group (EIT-guided airway clearance) or the control group (standard airway clearance). No modifications to study methods or eligibility criteria were made after trial initiation.

Participants

Patient recruitment was conducted between July 2022 and December 2024. Eligible participants were adults (≥18 years) who met the Berlin definition of ARDS, most commonly secondary to pneumonia. Inclusion criteria were: persistent hypoxemia with ratio of arterial oxygen tension to the fraction of inspired oxygen (PaO₂/FiO₂) <150 mmHg for at least 6 hours despite optimized oxygen therapy; arterial oxygen saturation (SpO₂) <90% prior to respiratory support (9), improving to >94% with HFNC or NIV; full consciousness (10); ability to tolerate prone positioning; and capacity to recognize and report discomfort (11). All enrolled patients were non-intubated and received either HFNC or NIV as their initial mode of respiratory support at randomization, ensuring a homogeneous non-invasive ARDS population. A minority of patients transitioned between HFNC and NIV during the ICU stay (e.g., initial NIV followed by HFNC after stabilization), reflecting routine clinical practice.

Exclusion criteria included unstable spine, pelvic, or long bone fractures; intracranial hypertension; severe arrhythmias or hemodynamic instability; abdominal trauma; extensive skin lesions precluding prone positioning; or refusal to undergo prone ventilation. Patients who died or were discharged early (<5 days ICU stay) were also excluded.

Randomization and allocation concealment

Random sequence generation was performed using a random digit table. Simple randomization without stratification or blocking was employed. Allocation concealment was ensured using sequentially numbered, opaque, sealed envelopes, which were opened only after baseline eligibility confirmation. The random sequence was generated by an independent research coordinator, while ICU nurses enrolled participants and assigned interventions.

Blinding of care providers and patients was not feasible due to the nature of the intervention. However, outcome assessors were blinded to group allocation. Because the interventions differed in mechanism (EIT-guided versus conventional imaging), blinding for intervention similarity was not applicable.

Interventions

Control group

Patients received standard chest physiotherapy (CPT) according to local ICU guidelines, including repositioning, manual percussion, nebulization, and vibration assisted clearance when secretion retention was present. These four components were performed every two hours. Nebulization consisted of isotonic saline or bronchodilator aerosol delivered via the HFNC or NIV interface. Chest radiography and computed tomography were used solely for diagnostic purposes. Prone positioning was prescribed for twelve-sixteen hours per day, with breaks as clinically indicated.

Experimental group

Patients in the intervention arm received an EIT guided CPT protocol using the PulmoVISTA 500 system (Dräger, Lübeck, Germany). The EIT belt was positioned at the 5th–6th intercostal space to enable real time monitoring of lung ventilation (Figure 1A). Ventilation distribution across four regions of interest (ROIs)—zones 1–2 (non-dependent) and zones 3–4 (gravity dependent)—was prespecified as the primary intra-patient guidance metric in the experimental arm to individualize CPT (Figure 1B), as it is the most validated and clinically interpretable parameter in awake prone patients. Other indices, such as the global inhomogeneity index, regional compliance, and end-expiratory lung impedance, were recorded but not analyzed in this trial. CPT components were identical to those in the control group, but their frequency, duration, and intensity were adjusted daily according to EIT findings. If EIT demonstrated dorsal atelectasis, prone positioning was extended to 16–20 hours per day.

Figure 1 EIT monitoring and interpretation in awake prone ventilation patients. (A) Placement of EIT electrodes at the intercostal space for continuous lung ventilation monitoring. (B) Segmentation of lung ventilation regions, where areas 1 and 2 represent non-gravity-dependent zones, and areas 3 and 4 correspond to gravity-dependent zones. (C) Normal lung inflation, indicated by the red arrows. (D) Areas of alveolar collapse, highlighted by the red arrows, indicating impaired ventilation. (E) Regions of alveolar overdistension, marked by red circles, suggestive of excessive ventilatory pressure. (F) Offline EIT-based analysis guiding optimal EPAP titration for prone ventilation patients. EIT, electrical impedance tomography; EPAP, expiratory positive airway pressure.

In addition, for patients receiving NIV, EIT was used to assist in titration of expiratory positive airway pressure (EPAP). Specifically, EIT enabled identification of the point at which end-expiratory lung volume ceased to decline effectively during stepwise EPAP reduction, thereby helping to avoid dropping external EPAP below the patient’s intrinsic PEEP. This approach aims to prevent de-recruitment, minimize excessive ventilation, and enhance patient comfort. ROI data was not acquired in the control arm and was not intended as a between-group comparative outcome.

Airway clearance techniques

Because patients undergoing awake prone ventilation retained spontaneous coughing ability, airway clearance was facilitated through external oscillation and patient-guided sputum clearance rather than positive expiratory pressure oscillation (12,13). Mechanical vibration-assisted clearance was selected over high-frequency chest wall oscillation to enhance comfort.

Protocol implementation

EIT-guided protocols were initiated within 24 hours of ICU admission and reassessed each morning at 09:00. CPT components were identical in both groups until EIT-guided adjustments were applied. Specific CPT adjustments were triggered by EIT findings: dorsal collapse prompted intensified vibration-assisted clearance and postural drainage, whereas ventral overdistension prompted reduction of oscillation intensity and adjustment of prone duration. Airway clearance strategies were developed collaboratively by physicians, respiratory therapists, and rehabilitation nurses based on EIT findings (Table 1). Daily indications for APP included PaO₂/FiO₂ <150 mmHg despite HFNC/NIV. Prolongation was considered if oxygenation improved but remained <200 mmHg. Stopping rules included sustained PaO₂/FiO₂ >250 mmHg or patient intolerance. EIT images were reviewed exclusively by the respiratory therapy team to guide CPT maneuvers. Attending physicians responsible for escalation of respiratory support (HFNC, NIV, or intubation) were blinded to EIT findings and made decisions solely on standard clinical criteria. Adjustments continued until prone ventilation was discontinued. All participating nurses received formal respiratory therapy training and certification.

Outcome measures

The effectiveness of airway clearance interventions was primarily assessed using three clinical parameters: secretion quantity and viscosity, cough strength, and changes in clinical symptoms. However, measuring secretion volume and viscosity in a clinical setting is inherently variable and difficult to standardize. Therefore, the primary outcome was the change in PaO₂/FiO₂ ratio from day 1 to day 5. Secondary endpoints included changes in oxygenation (day 1 to day 3), patient comfort, prone duration, ICU stay, duration of HFNC/NIV support, and treatment failure (defined as progression to intubation and invasive ventilation).

Each outcome measure and its method of assessment are described as follows:

• PaO₂/FiO₂ ratio: PaO₂/FiO₂ ratio was defined as the ratio of arterial oxygen tension (PaO₂) to the fraction of inspired oxygen (FiO₂), with normal values ranging from 400 to 500 mmHg (1 mmHg =0.133 kPa). Measurements were recorded on days 1, 3, and 5 post-interventions in both groups.
• Patient comfort: patient comfort was assessed using a validated 0–10 numerical rating scale, reflecting perceived breathing difficulty, discomfort, and pain.At the conclusion of prone ventilation, patient comfort was assessed using a numerical rating scale (0–10), with higher scores indicating greater comfort. Comfort scores were compared between groups.
• Duration of prone ventilation daily prone ventilation duration was recorded and averaged. Intergroup comparisons were conducted on days 1, 3, and 5 post-intervention.
• ICU length of stay was defined as the time from ICU admission to discharge. Comparisons were made between the two groups. No changes to pre-specified outcome measures were made during the trial.
• Duration of HFNC/NIV support the total duration of HFNC or NIV support was recorded for each patient until discontinuation or escalation to intubation.

Sample size calculation

Sample size was estimated using the two-sample t-test formula: N₁ = N₂ = 2[(Zα + Zβ)σ/δ]². Preliminary data from 15 patients per group indicated the following: Experimental group: 322.47±67.49 mmHg; Control group: 274.33±56.92 mmHg. With α=0.05, power =0.90, and pooled standard deviation =66.05, the estimated sample size per group was 40. Accounting for a 15% attrition rate, the final sample size was set at 46 per group, totaling 92 patients. No interim analyses or stopping guidelines were specified.

Data collection and statistical analysis

Oxygenation indices were collected daily at 05:00 via arterial blood gas analysis. Prone ventilation duration and ICU length of stay were recorded by nursing staff. Two blinded nurses jointly conducted comfort assessments. Data analysis was performed using SPSS version 27.0. Continuous variables were expressed as mean ± standard deviation and compared using independent-sample t-tests. Categorical variables were analyzed using chi-squared tests. Repeated measures ANOVA was used to evaluate differences in oxygenation indices and prone ventilation duration across multiple time points, with Bonferroni correction applied for post hoc comparisons. Statistical significance was set at α=0.05. No subgroup or adjusted analyses were performed.

Results

Participant flow

Between July 2022 and December 2024, 92 patients were enrolled and randomized (46 per group). Of these, five did not complete the study. In the control group, two patients withdrew due to fear of prone positioning and one at the request of family members; in the EIT group, two patients withdrew at the request of family members. Because consent for continued participation was revoked, their data were not available for efficacy analysis. The primary analysis was therefore conducted in a modified intention-to-treat population, defined as all randomized patients with at least one post-baseline assessment. The trial was completed as planned, meeting the recruitment target without early termination or protocol modifications. Details of participant flow are shown in Figure 2.

Figure 2 CONSORT flow diagram of patient enrollment, randomization, and analysis.

Baseline characteristics

Baseline characteristics, including distribution of respiratory support modalities, were comparable between groups (Table 2). At enrollment, all patients received either HFNC or NIV as their initial mode of non-invasive respiratory support. Table 2 reflects this distribution at the time of randomization. During the ICU stay, some patients transitioned between HFNC and NIV; however, all patients were managed exclusively with these two modalities, and no patient received supplemental oxygen alone.

Primary outcome: the change of PaO₂/FiO₂ ratio on day 5

The PaO₂/FiO₂ ratio showed significant improvement over time in both groups. Repeated measures ANOVA revealed significant main effects for both group and time (P<0.05), as well as a significant group-by-time interaction (F=4.105, P<0.05).

PaO₂/FiO₂ ratios improved significantly from baseline in both groups at days 1, 3, and 5 (P<0.05). The experimental group demonstrated significantly higher PaO₂/FiO₂ ratios than the control group at days 3 and 5 (P<0.05), with a mean between-group difference of 31.5 mmHg on day 5, the pre-specified primary endpoint (Table 3).

Secondary outcome: duration of prone ventilation

Prone ventilation duration increased significantly in both groups following intervention. Repeated measures ANOVA identified significant effects for group and time (P<0.001), along with a significant group-by-time interaction (F=6.133, P<0.05).

Multiple comparisons across time points revealed that both groups maintained significantly longer prone ventilation durations on days 3 and 5 compared to day 1 (P<0.05). The experimental group consistently exhibited longer durations than the control group at all measured time points. For instance, on day 5, the experimental group averaged 13.18±3.49 hours, compared to 8.98±3.26 hours in the control group (P<0.001) (Table 4).

Secondary outcomes: patient comfort and ICU length of stay

Post-intervention patient comfort scores, assessed on a 0–10 numerical rating scale, were significantly higher in the experimental group (6.98±1.05) than in the control group (5.86±1.15), P<0.001.

No statistically significant difference was observed in ICU length of stay between groups (experimental: 13.11±4.79 days; control: 14.40±6.31 days; P>0.05) (Table 5).

Ancillary analyses

With respect to CPT, the EIT group underwent more targeted repositioning maneuvers (mean 3.2 vs. 2.1 per day, P<0.05) and more frequent vibration assisted sessions (mean 2.8 vs. 1.9 per day, P<0.05), whereas the overall daily frequency of CPT did not differ significantly between groups.

At day 5, mean FiO₂ requirements were 0.52±0.08 in the EIT group vs. 0.54±0.09 in controls (P>0.05). HFNC flow rates averaged (48.2±6.5) vs. (47.5±7.1) L/min (P>0.05), and NIV EPAP averaged (7.8±1.2) vs. (8.0±1.3) cmH₂O (P>0.05). These findings indicate that extended prone duration in the EIT group was attributable to improved tolerance rather than increased support.

Failure rates, defined as progression to endotracheal intubation and IMV, were 13.6% (6/44) in the EIT group and 18.6% (8/43) in the control group (P=0.57). No subgroup analyses, adjusted analyses, or exploratory outcomes were conducted.

Harms

No serious adverse events or unintended effects related to the interventions were reported in either group. Minor discomforts—including transient coughing and belt pressure marks—were noted in three patients from the experimental group and two from the control group. These symptoms were self-limiting and did not necessitate discontinuation of the intervention.

Discussion

This prospective randomized controlled trial demonstrated that an EIT-guided airway clearance protocol significantly improves oxygenation, extends prone positioning duration, and enhances patient comfort in awake ICU patients undergoing prone ventilation. EIT provides real-time assessment of lung function, making it a valuable tool for evaluating pulmonary status. By integrating continuous bedside EIT with individualized airway management, the intervention enables real-time adjustment of ventilation parameters and precise evaluation of regional lung function. These findings support the clinical utility of EIT-guided strategies and highlight their potential role in a personalized framework for respiratory care in critically ill patients.

EIT-guided airway clearance improves oxygenation

Within-group analyses revealed significant improvements in PaO₂/FiO₂ ratios on days 1, 3, and 5 post-intervention in both groups, reaffirming the efficacy of prone ventilation in enhancing oxygenation. Previous studies by Shuhe, Yang, and colleagues have similarly demonstrated that prone positioning markedly improves oxygenation and lung ventilation (14,15). These benefits are likely attributable to dorsal alveolar recruitment, improved ventilation-perfusion matching, increased respiratory system compliance, and enhanced postural drainage.

Between-group comparisons further revealed that the experimental group achieved superior oxygenation indices on days 3 and 5, suggesting that EIT-guided airway clearance provides additional clinical advantages. Airway clearance techniques facilitate secretion removal, thereby reducing the risk of respiratory infections, airway obstruction, and dyspnea through lung expansion, airway oscillation, suctioning, postural drainage, and assisted coughing (16). Importantly, no cases of ICU-acquired respiratory infection occurred during the study period, which further supports the safety of the intervention and suggests that effective airway clearance may have contributed to this outcome. Although the absolute improvement of 31.5 mmHg in PaO₂/FiO₂ on day 5 may appear modest, it reached statistical significance and should not be underestimated in the context of non-intubated ARDS patients. Even incremental improvements in oxygenation can reduce the likelihood of intubation, prolong tolerance of non-invasive support, and provide a therapeutic window for adjunctive interventions. Thus, the observed effect is both statistically robust and clinically meaningful.

Traditional imaging modalities such as chest X-ray and CT lack real-time dynamic assessment and are often reliant on subjective clinical judgment. In contrast, EIT offers continuous bedside monitoring of lung ventilation, enabling precise evaluation and individualized airway clearance interventions. Prior research has shown that EIT effectively tracks changes in ventilation distribution among patients undergoing APP, where improved spatial and temporal homogeneity enhances oxygenation in non-intubated individuals (17). Through real-time impedance imaging, clinicians can promptly detect lung collapse or overdistension and tailor interventions—such as repositioning or vibration-assisted clearance—while immediately assessing their impact via EIT. Moreover, EIT’s ability to quantify regional ventilation allows for targeted recruitment of under-ventilated lung segments, optimizing ventilation–perfusion balance and potentially improving clinical outcomes.

EIT-guided airway clearance enhances patient comfort

The significantly higher comfort scores observed in the experimental group suggest that EIT-guided airway clearance contributes to improved patient tolerance during prone ventilation. This validated numerical rating scale reflects perceived breathing difficulty, discomfort, and pain, ensuring that the comfort assessment is clinically meaningful. Previous studies have similarly emphasized the importance of integrating patient-centered outcomes with physiological measures, highlighting that improvements in comfort often parallel enhancements in respiratory mechanics and gas exchange (18).

HFNC has been shown to increase end-expiratory lung volume (EELV), as confirmed by EIT monitoring, thereby reducing respiratory rate and improving oxygenation. However, studies on patients with acute hypoxemic respiratory failure indicate that while HFNC flow rates exceeding 60 L/min can significantly increase end-expiratory lung volume—particularly in non-dependent lung regions—they may also reduce patient comfort due to limitations in humidification systems (19,20). Given the variability in patient response, previous studies have suggested that EIT may be useful for dynamically adjusting HFNC settings to prevent overdistension and improve comfort (21,22); however, this was not the objective of the present trial. Although HFNC benefits most patients, careful titration is essential to prevent lung injury in vulnerable individuals (23). Prior studies have further underscored the utility of EIT in monitoring HFNC applications (22).

In patients receiving NIV, factors such as air leakage and variable patient effort can compromise the reliability of mechanical parameters. A feasibility study using EIT to evaluate regional expiratory time constants in severe respiratory failure found a strong correlation between ventilator-set PEEP and regional expiratory dynamics (24). Kostakou et al. demonstrated that NIV settings guided by these regional expiratory time constants can reduce overventilation, dead space, and the work of breathing in patients with COPD (25).

In our study, EIT was instrumental in identifying the point at which end-expiratory lung volume ceased to decline effectively during EPAP titration in NIV patients. When external EPAP dropped below the patient’s intrinsic PEEP, EIT detected the threshold, thereby preventing excessive ventilation and enhancing comfort. This real-time titration of ventilatory support enabled by EIT represents a significant advancement in precision respiratory care.

EIT-guided airway clearance prolongs prone ventilation duration

Discomfort is a major limiting factor in maintaining prone positioning, as evidenced by shorter prone durations reported in previous studies (26). Awake patients may struggle to tolerate prolonged prone ventilation when comfort is compromised. By combining more tolerable oxygenation modalities (HFNC or NIV) with real-time EIT monitoring, our protocol improved patient comfort and consequently extended prone ventilation duration.

The experimental group consistently maintained longer prone ventilation durations than the control group at all measured time points. However, this difference largely reflects adherence to the EIT-guided protocol and should be considered a feasibility outcome rather than a definitive efficacy endpoint. In contrast, ICU length of stay showed no meaningful difference between groups. This pattern likely reflects local practice, where patients are typically kept in the ICU until hypoxemia has resolved and stable weaning from HFNC or NIV is achieved, regardless of intubation status. Extended ICU stays (mean 13–14 days) were largely attributable to persistent hypoxemia, coexisting comorbidities, and limited availability of step-down units. Although failure rates were numerically lower in the EIT group, the difference was not statistically significant, likely due to sample size limitations. Taken together, the results indicate that although EIT-guided CPT appears to enhance comfort and extend prone tolerance, its effect on ICU length of stay and failure rates remains uncertain, underscoring the need for larger multicenter trials to validate these potential benefits. More broadly, the study underscores the importance of integrating continuous, individualized monitoring into respiratory care protocols to address comfort-related limitations and optimize clinical outcomes.

Clinical integration of EIT in prone ventilation and precision nursing

The technical advantages of EIT make it particularly well-suited for monitoring lung function during prone positioning, enabling early identification of patients who may benefit from this intervention. This capability offers valuable guidance for optimizing clinical treatment and nursing strategies. However, standardized clinical criteria and procedural guidelines—such as ventilation mode selection and PEEP titration—remain underdeveloped. Further research is needed to establish comprehensive protocols for clinical application.

EIT-guided airway clearance strategies have shown promise in improving lung pathology, reducing airway resistance, and enhancing pulmonary compliance. In this study, specialized respiratory therapy nurses and respiratory therapists were the primary implementers of EIT assessments. Their proficiency in EIT-related knowledge was comparable to that of physicians, enabling effective integration of this technology into critical care nursing. Incorporating EIT into routine nursing workflows can help address clinical challenges more efficiently.

Expanding the scope of nursing practice to include medical imaging technologies such as EIT will facilitate the implementation of precision care strategies, ultimately improving patient outcomes in critical care settings.

Limitations

There are several limitations in this study that warrant consideration. First, as a single-center trial, its external validity is limited, and the findings may not be generalizable to other institutions or patient populations. Second, the lack of blinding introduces potential assessment bias, particularly for subjective outcomes such as patient comfort. Although the 0–10 numerical rating scale is validated and widely used in ICU research, it remains a subjective tool and may be influenced by patient mood, emotional state, or communication ability; this limitation should be considered when interpreting the comfort outcomes. Third, the study focused exclusively on short-term clinical indicators, leaving the long-term effectiveness and safety of EIT-guided airway clearance protocols unexplored. Moreover, our study population—non-intubated ARDS patients—differs from the classical mechanically ventilated ARDS cohorts. This heterogeneity, combined with the single-center design, may further limit generalizability. Nevertheless, randomization, standardized eligibility criteria, and consistent intervention protocols minimized potential confounders. Fourth, excluding patients with ICU stay <5 days may have introduced selection bias, as these patients often represent either very severe or very mild cases. Finally, the requirement for specialized EIT equipment and trained personnel may pose barriers to widespread implementation, especially in resource-constrained settings.

Conclusions

This randomized controlled trial demonstrates that an EIT-guided airway clearance protocol significantly improves oxygenation, enhances patient comfort, and prolongs prone ventilation duration in awake ICU patients. EIT-guided CPT improved oxygenation, comfort, and prone duration; however, its impact on long-term outcomes such as ICU stay and intubation rates requires further investigation. While further research is needed to validate these findings in larger multicenter cohorts, this study represents one of the first RCTs exploring EIT-guided CPT in non-intubated ARDS patients, highlighting its potential role in personalized respiratory management. At the same time, further studies are warranted to establish standardized clinical indicators—such as optimal ventilator mode selection and PEEP titration—for broader application.

The integration of EIT into routine critical care, supported by trained nurses and respiratory therapists, demonstrates both feasibility and clinical value. Incorporating imaging-based precision care into nursing practice may help close existing gaps in respiratory management and improve ICU outcomes. Overall, EIT emerges as a promising cornerstone technology for advancing individualized, data-driven critical care.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the CONSORT reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1473/rc

Trial Protocol: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1473/tp

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1473/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1473/prf

Funding: This work was supported by the Tianjin Municipal Health Science and Technology Project (grant No. TJWJ2022XK028 to X.W.) and the Tianjin Key Medical Discipline (Specialty) Construction Project (No. TJYXZDXK-3-021C to X.W.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1473/coif). X.W. reports that this work was supported by the Tianjin Municipal Health Science and Technology Project (grant number: TJWJ2022XK028) and the Tianjin Key Medical Discipline (Specialty) Construction Project (No. TJYXZDXK-3-021C). The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Tianjin Third Central Hospital (No. IRB2024-038-02) and informed consent was obtained from all participants or their legally authorized representatives.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Scholten EL, Beitler JR, Prisk GK, et al. Treatment of ARDS With Prone Positioning. Chest 2017;151:215-24. [Crossref] [PubMed]
2. Rampon GL, Simpson SQ, Agrawal R. Prone Positioning for Acute Hypoxemic Respiratory Failure and ARDS: A Review. Chest 2023;163:332-40. [Crossref] [PubMed]
3. Papazian L, Munshi L, Guérin C. Prone position in mechanically ventilated patients. Intensive Care Med 2022;48:1062-5. [Crossref] [PubMed]
4. Al-Mhanna SB, Batrakoulis A, Hofmeister M, et al. Psychophysiological Adaptations to Exercise Training in COVID-19 Patients: A Systematic Review. Biomed Res Int 2024;2024:3325321. [Crossref] [PubMed]
5. Olmos M, Fuentes N, Busico M, et al. Effectiveness of bundle of care on tolerance of awake-prone positioning in patients with acute respiratory failure. A multicenter observational study. Intensive Care Med 2025;51:332-41. [Crossref] [PubMed]
6. Luo J, Pavlov I, Tavernier E, et al. Awake Prone Positioning in Adults With COVID-19: An Individual Participant Data Meta-Analysis. JAMA Intern Med 2025;185:572-81. [Crossref] [PubMed]
7. Sánchez Romero EA, Alonso Pérez JL, Vinuesa Suárez I, et al. Spanish experience on the efficacy of airways clearance techniques in SARS-CoV-2 (COVID-19) at intensive care unit: An editorial and case report. SAGE Open Med Case Rep 2022;10:2050313X221112507.
8. Puel F, Crognier L, Soulé C, et al. Assessment of electrical impedance tomography to set optimal positive end-expiratory pressure for veno-venous ECMO-treated severe ARDS patients. J Crit Care 2020;60:38-44. [Crossref] [PubMed]
9. Cohen D, Wasserstrum Y, Segev A, et al. Beneficial effect of awake prone position in hypoxaemic patients with COVID-19: case reports and literature review. Intern Med J 2020;50:997-1000. [Crossref] [PubMed]
10. Bower G, He H. Protocol for awake prone positioning in COVID-19 patients: to do it earlier, easier, and longer. Crit Care 2020;24:371. [Crossref] [PubMed]
11. Jiang LG, LeBaron J, Bodnar D, et al. Conscious Proning: An Introduction of a Proning Protocol for Nonintubated, Awake, Hypoxic Emergency Department COVID-19 Patients. Acad Emerg Med 2020;27:566-9. [Crossref] [PubMed]
12. Herrero-Cortina B, Lee AL, Oliveira A, et al. European Respiratory Society statement on airway clearance techniques in adults with bronchiectasis. Eur Respir J 2023;62:2202053. [Crossref] [PubMed]
13. Pyszora A, Lewko A. Non-pharmacological Management in Palliative Care for Patients With Advanced COPD. Front Cardiovasc Med 2022;9:907664. [Crossref] [PubMed]
14. Yang S, Sun Q, Yuan X, et al. Effect of prone position on ventilation-perfusion matching in patients with moderate to severe ARDS with different clinical phenotypes. Respir Res 2025;26:70. [Crossref] [PubMed]
15. Liao X, Meng L, Zeng Z. Prone position ventilation for the relief of acute respiratory distress syndrome through improved pulmonary ventilation: Efficacy and safety. Nurs Crit Care 2024;29:255-73. [Crossref] [PubMed]
16. Annoni S, Bellofiore A, Repossini E, et al. Effectiveness of chest physiotherapy and pulmonary rehabilitation in patients with non-cystic fibrosis bronchiectasis: a narrative review. Monaldi Arch Chest Dis 2020;
17. Wang J, Chen C, Zhao Z, et al. Awake prone positioning and ventilation distribution as assessed by electric impedance tomography in patients with non-COVID-19 acute hypoxemic respiratory failure: A prospective physiology study. J Intensive Med 2025;5:43-50. [Crossref] [PubMed]
18. Cammarota G, Simonte R, De Robertis E. Comfort During Non-invasive Ventilation. Front Med (Lausanne) 2022;9:874250. [Crossref] [PubMed]
19. Basile MC, Mauri T, Spinelli E, et al. Nasal high flow higher than 60 L/min in patients with acute hypoxemic respiratory failure: a physiological study. Crit Care 2020;24:654. [Crossref] [PubMed]
20. Ni Z, Zhou Y, Tang N, et al. Comparison of actual performance in humidification among different high-flow nasal cannula devices: a bench study. Front Med (Lausanne) 2023;10:1209977. [Crossref] [PubMed]
21. Zhao Z, Chang MY, Zhang T, et al. Monitoring the Efficacy of High-Flow Nasal Cannula Oxygen Therapy in Patients with Acute Hypoxemic Respiratory Failure in the General Respiratory Ward: A Prospective Observational Study. Biomedicines 2023;11:3067. [Crossref] [PubMed]
22. Li Z, Zhang Z, Xia Q, et al. First Attempt at Using Electrical Impedance Tomography to Predict High Flow Nasal Cannula Therapy Outcomes at an Early Phase. Front Med (Lausanne) 2021;8:737810. [Crossref] [PubMed]
23. Zhang R, He H, Yun L, et al. Effect of postextubation high-flow nasal cannula therapy on lung recruitment and overdistension in high-risk patient. Crit Care 2020;24:82. [Crossref] [PubMed]
24. Karagiannidis C, Waldmann AD, Róka PL, et al. Regional expiratory time constants in severe respiratory failure estimated by electrical impedance tomography: a feasibility study. Crit Care 2018;22:221. [Crossref] [PubMed]
25. Kostakou E, Barrett N, Camporota L. Electrical impedance tomography to determine optimal positive end-expiratory pressure in severe chronic obstructive pulmonary disease. Crit Care 2016;20:295. [Crossref] [PubMed]
26. Ehrmann S, Li J, Ibarra-Estrada M, et al. Awake prone positioning for COVID-19 acute hypoxaemic respiratory failure: a randomised, controlled, multinational, open-label meta-trial. Lancet Respir Med 2021;9:1387-95. [Crossref] [PubMed]